The bidomain model describes the three-dimensional, syncytial (cable-like) electrical properties of cardiac tissue, and thereby provides a physiologically realistic link between the sub-micron spatial scale associated with molecular electrophysiology and the millimeter and centimeter scales of cardiac activation and fibrillation. The preceding five years of work demonstrated that the anisotropic bidomain can explain the virtual electrode and magnetic field patterns observed with point stimulation. This model with fiber rotation and curvature has replaced the sawtooth model as the most likely contender for describing the response of the heart to defibrillation-strength shocks. The bidomain model with accurate membrane kinetics can reproduce almost all features observed in macroscopic cardiac electrical activity. The research objective is to continue using the bidomain model and a suite of advanced experimental, analytical, and numerical techniques to probe the relationship between cardiac tissue architecture and cardiac electrical activity, with a particular focus on the production of the cardiac magnetic field and the response of the heart to electrical stimulation. The specific aims are to explore the mechanisms by which externally applied shocks alter the transmembrane potential distribution over macroscopic regions of cardiac tissue; (2) develop measurement and analytical techniques to determine realistic values for the key bidomain parameters; (3) measure the cardiac magnetic field from isolated heart preparations to explore the relationships between the transmembrane potential, stimulus and action currents, and fiber architecture and electrical anisotropy; (4) explore the relation between the cardiac bi-domain, phase singularities, and sequential stimuli during reentry, fibrillation, and defibrillation; (5) study the dynamics of damped propagation and its role in formation and termination of reentrant propagation; (6) devise and apply advanced optical and magnetic instrumentation to study the electrical activity of isolated cardiac tissue; (7) explore the capabilities and limitations of phase space analysis and image processing to understand the dynamic behavior of stimulation, reentry and defibrillation; and (8) continue to develop and refine numerical cardiac bidomain models. This research may lead to more efficient cardiac pacemakers and defibrillators and improved magnetocardiographic diagnosis of coronary heart disease.